Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy. Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.; San Diego; Ft. Walton Beach, Florida; Ann Arbor, Michigan; London; Stuttgart; Munich; Stockholm; Bangalore; Seoul; and Tokyo. Learn more at applied.co http://applied.co. We are an in-office company, and our expectation is that full-time employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions ABOUT THE ROLE AND TEAM We are looking for software engineers to help build the backbone of Neural Simulation, our state-of-the-art product for turning real-world driving data into high-fidelity simulation environments. As part of this team, you will design and develop the systems that power large-scale reconstruction, synthetic data generation, and log augmentation, along with the ML pipelines used to train and validate autonomy systems. You will work on distributed systems that transform real-world data into simulation environments and generate high-quality labeled data at scale, working alongside senior engineers on system design across compute, storage, and data pipelines. This role is ideal for engineers who want to grow at the intersection of large-scale distributed systems and machine learning, and who are excited to help scale a state-of-the-art product while building new capabilities that solve the hardest data and platform gaps in Physical AI. AT APPLIED INTUITION, YOU WILL: - Build and maintain scalable systems for Neural Simulation, including closed loop simulation and log augmentation workflows - Develop services and data pipelines that process and manage large-scale data - Contribute to infrastructure for ML workflows, including: - Training pipelines - Evaluation and validation systems - Model inference pipelines - Implement and optimize storage solutions for structured, unstructured, and multimodal data (e.g., sensor, 3D, logs) - Improve system reliability, observability, and performance across distributed services - Collaborate closely with Infra, Autonomy, Research and other product teams to deliver end-to-end solutions - Own features and components end to end, from design through deployment, and contribute to architecture discussions WE'RE LOOKING FOR SOMEONE WHO HAS: - 2+ years of experience shipping production software - A minimum of a Bachelor's degree in computer science, computer engineering, or equivalent practical experience - Experience building backend services or data pipelines, and working with data storage systems (such as SQL, NoSQL, or data lakes) - Familiarity with cloud platforms (AWS, GCP, or Azure) and containerized systems (Docker, Kubernetes) - Experience with backend development in languages such as Python and Go - Solid software engineering fundamentals and strong problem-solving skills NICE TO HAVE: - Experience with distributed systems at scale - Experience building or supporting ML training and serving infrastructure - Experience with GPU workloads and batch orchestration (e.g., Kubernetes jobs, Ray, Airflow) - Experience with synthetic data generation or data augmentation for ML - Familiarity with computer vision, 3D reconstruction (e.g., Gaussian Splatting), or sensor simulation (camera, LiDAR, radar) - Experience with autonomous driving or robotics systems Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles. Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws. FOR US-BASED ROLES: Applied Intuition is committed to providing an accessible and inclusive application and interview experience to applicants who are disabled veterans and other applicants with disabilities or medical conditions. Reasonable accommodations are available, requesting an accommodation will not affect your candidacy in any way, and you are not required to disclose the nature of your disability or medical condition in order to make a request. If you require an accommodation please contact careers@applied.co. We will work with you!